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Bi-objective Synthesis of CCUS System Considering Inherent Safety and Economic Criteria

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Abstract

Carbon capture, utilization, and storage (CCUS) is a carbon management strategy to mitigate CO2 emissions from point sources. It is a crucial technology for local low-carbon development. Regional source-sink models have been developed based on the carbon life cycle. In this work, a bi-objective mixed-integer nonlinear programming model is developed for optimizing the carbon management network of a regional CCUS system. The goal is to develop a set of solutions that achieve various trade-offs between economic and safety criteria, with the latter based on overall annual risk. The model considers different point sources of CO2 emissions, multiple capture technologies, and four utilization sinks (e.g., greenhouse, urea synthesis, methanol production, and enhanced oil recovery). The model was applied and demonstrated in Dongying, China.

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Data Availability

The model code and data used in this work are available upon reasonable request addressed to the corresponding author.

Abbreviations

s ∈ S:

The sources of flue gases emissions

t ∈ T:

The units for trapping and treating flue gases

u ∈ U:

The units without any treatment of flue gas

k ∈ K:

The sinks for fixed CO2

r ∈ RISK:

Different risk types

i ∈ COMPON:

The components in process

j ∈ UNITS:

The units in process

\({C}_{\mathrm{base}}\) :

Base cost in the carbon dioxide pipeline capital cost

\({C}_{k}^{\mathrm{sink}}\) :

Cost of technical treatment of CO2 in a sink

\({C}_{s}^{T}\) :

The cost parameter of the treatment unit

\({C}^{\mathrm{tax}}\) :

Tax value cost parameter per t CO2

\(CRF\) :

Capital recovery factor of total cost per year

\(Elec\) :

Electricity fees

\({f}_{j}^{\mathrm{fail}}\) :

Failure rate of different units in the process

\({G}_{i,r}\) :

Explosively, toxicity and whether the composition is flammable measure

\({G}_{k}^{\mathrm{max}}\) :

The maximum flow requirement for sinks

\({G}_{\mathrm{base}}\) :

Base length for carbon dioxide pipeline calculation

\({G}_{\mathrm{pipe},s,k}\) :

The distance between source and sink

\({L}_{h}\) :

The liquid release distance from the pipeline

\({L}_{s}\) :

The lower limit of available flow from the source

\({L}_{s,k}\) :

The lower flow limit of pipe flow

\({M}_{\mathrm{base}}\) :

Base flow of CO2 used to calculate pipeline capital costs, in t CO2 per day

\({M}_{s}\) :

The upper bound flow available from the source

\({M}_{s,k}\) :

The upper flow limit of pipe flow

\(NCRT\) :

The net carbon reduction target

\(OM\) :

Pipeline annual operation and maintenance cost rate

\({P}^{\mathrm{comp}}\) :

Compressor power parameters

\({P}_{d}\) :

The average value of population density

\({Pf}_{h}\) :

Probability of occurrence of event h

\({P}^{\mathrm{pump}}\) :

Pump power parameters

\({S}_{h}\) :

Affected area of pipeline release

\({y}_{u}\) :

Composition of the untreated source

\({y}_{s}\) :

The raw source component located at a source

\({y}_{s,t}\) :

Composition of the treated source

\({Z}_{k}^{\mathrm{min}}\) :

The minimum composition requirement for sink

\(\alpha\) :

CO2 flow rate scaling factor

\(\beta\) :

Distance scaling factor

\({\gamma }_{t}\) :

The carbon footprint parameters related to energy use

\({\varepsilon }_{p}\) :

The carbon footprint parameter related to electricity use

\({\varepsilon }_{t}\) :

The carbon removal efficiency of treatment units

\({\vartheta }_{t}\) :

The sink efficiency factor

\({AI }_{r,i,j}\) :

The severity of consequences

\({C}_{s,k}^{\mathrm{Compression}}\) :

The compression and preparation cost from source to sink

\({C}_{s,k}^{\mathrm{compressor}}\) :

The total cost of the compressor from source to sink

\({C}_{s,k}^{ \mathrm{pump}}\) :

The total cost of the pump from source to sink

\({C}_{s,k}^{\mathrm{Sinks}}\) :

The cost of processing CO2 in a given sink

\({C}_{s,k}^{\mathrm{Taxes}}\) :

Total income from CO2 tax value

\({C}_{s,k}^{\mathrm{Transportation}}\) :

The transportation cost from source to sink

\({C}_{s,k}^{\mathrm{Treatment}}\) :

The treatment cost from the source to the sink

\({F}_{s,k}\) :

The flow into sink

\({m}_{i}\) :

The mass of substances in components (t)

\(R\) :

Total risk level

\({R}^{\mathrm{capture}}\) :

Total risk of carbon capture process

\({R}^{\mathrm{storage}}\) :

Total risk of carbon storage process

\({R}^{\mathrm{transport}}\) :

Total risk of carbon transport process

\({R}^{\mathrm{utilization}}\) :

Total risk of carbon utilization process

\({R}_{r,i,j}\) :

Risks in each unit and component corresponding to various risks

\({R}_{s}\) :

The raw source flow of a source s

\({T}_{s,k,t}\) :

The flow of treatment units

\({U}_{s,k}\) :

The flow of untreated units

\(Z\) :

Annual total cost

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Funding

The authors would like to thank the financial support provided by the National Key R&D Program of China (2020YFE0201400) and the National Natural Science Foundation of China (52270184).

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Authors and Affiliations

  1. School of Environment and Safety Engineering, Qingdao University of Science and Technology, Qingdao, 266042, China

    Fei Wang, Fang Wang & Xiaoping Jia

  2. Sino-Geman Engineering College, Qingdao University of Science and Technology, Qingdao, 266042, China

    Fang Wang

  3. Department of Chemical Engineering, De La Salle University, 0922, Manila, Philippines

    Kathleen B. Aviso & Raymond R. Tan

  4. School of Chemistry and Chemical Engineering, Hefei University of Technology, Hefei, 230009, China

    Zhiwei Li

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  1. Fei Wang
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  2. Fang Wang
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Correspondence to Fang Wang or Xiaoping Jia.

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Wang, F., Wang, F., Aviso, K.B. et al. Bi-objective Synthesis of CCUS System Considering Inherent Safety and Economic Criteria. Process Integr Optim Sustain 7, 1319–1331 (2023). https://doi.org/10.1007/s41660-023-00344-9

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